I understand that, but why is using copyrighted images to train a model be any more illegal than studying copyrighted paintings in art school? Copyright doesn't prevent consumption or interpretation, simply reproduction.
Copyright can be fairly flexible in interpreting what constitutes a derivative work. The Getty water is evidence that an image belongs to Getty. If someone produces an image with the watermark and gets sued, they could say "your honor, I know it looks like I copied that image but let's consider the details of how my hypercomplex whatsit work..." and then judge, say a nontechnical person, looks at the defendant and say "no, just no, the court isn't going to look at those details, how could court do that?". Or maybe the court would consider it only if you paid 1000 neutral lawyer-programmers to come up with a judgement, at a cost of millions or billions per case.
Another scenario, what if i create a painting of a river by hand in acrylic and also draw a getty-watermark-looking thing on top using acrylic? As for why, i would put it there as an integral part of the piece, to allude to the fact of how corporations got their hands over even the purest things that have nothing to do with them, with the fake watermark in acrylic symbolizing it. You can make up any other reason, this is just the one i thought of as i was writing this. It wont look exactly like the real getty watermark, it will be acrylic and drawn by hand, so pretty uneven with colors being off and way less detailed. Doesn't feel like fraud to me.
What if i create a painting of a river by hand in acrylic and also draw a getty-watermark-looking thing on top using acrylic? As for why, i would put it there as an integral part of the piece, to allude to the fact of how corporations got their hands over even the purest things that have nothing to do with them, with the fake watermark in acrylic symbolizing it.
A human artist might well do that and make that defense in court. For all anyone knows, some GPT-3-derived-thing might go through such a thought process also (though it seems unlikely). However, the GPT-3-derived-thing can't testify in court concerning it's intent and that produces problems. And it's difficult for anyone to make this claim for it.
Edit: Also, if instead of a single work (of parody), you produced a series of your own stock photos, used the Getty Watermark and invited people to use them for stock photo purposes, then your use of the copyrighted Getty Watermark would no longer fall under the parody exception for fair use.
In both cases, you take a series of bytes (the image data / the library source code) that is ultimately crucial to the functioning of your software, combine it with your own original code you wrote (training / compilation), and end up with a new output (the trained model / the binary executable) that is distinct from any of the original sources.
If you use a GPL'd library in your software, then it's uncontroversial to say that you have to follow the terms of the GPL. You can't say "well actually, the compiler is just reading your source code and learning what sort of binary it should produce, just like a human learns by studying source code, so I actually don't have to follow your licensing terms". No one would buy that. You clearly used that library, so you have to obey whatever terms come along with it.
Why is it fine to ignore the licensing terms for image data you incorporate into your software, but not third-party source code that you incorporate?
What if I read the code, understand its concepts, and re-implements another library that provide similar functionality without directly linking to the original repository, that is not an infringement, and actually how open source community has always been operating, like MariaDB to MySQL, or any projects that markets themselves as 'open source alternative' of some commercial software.
I would argue, the diffusion models are really good, it is possible that they capture the essentials of drawing that they learn no different than a human. Put in another way, it masters the imaging process at fundamental level
I agree, that's fine.
The analogous situation with image generators would be if the companies that trained the models had a human artist look at every image in their dataset, paint a unique but similar image, and then feed all of those images into the model, so that no copyrighted images were used in training without permission. But that's obviously not what they did. They just fed in the images unaltered, without getting permission.
It might be… which is why famously wine developers don't look at leaked windows code.
In art is very common that some author review their own work and made several paintings of the same subject. Artists made several attempts to conquer a panting, they draw studios or use different mediums. Photographers reproduce one portrait 20 years later to see how the subject changed. If you insert an IA image in the middle and copyright it, then any posterior painting on the same subject, even by the original author, would became derivative of the IA image that replaced it. This could even go so far as excluding the artists to review their most successful works.
Even if it was plausible to believe the mechanics of how human brains process art was particularly similar to a diffusion model or GAN, I don't see "but human brains are deterministic functions of their inputs too" as being a successful legal argument any time soon. You'd have to throw out rather more of the legal system than just copyright if those arguments start to prevail...
You just described how modern browser cache images.
The diffusion model is revolutionary at scale, but doesn't mean it is doing anything drastically different than what is allowed right now, e.g. any AI based image beautifying/denoise filter, just the scale changes everything.